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Agent Skill · 研究检索

chat-rooom(聊天室)

chat-rooom 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

chat-rooom 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,432。

总安装 9,381周安装 387GitHub Stars 公开资料未说明下载 3,065核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:chat-rooom(聊天室)
来源仓库:https://github.com/ivangdavila/chat-rooom
安装命令:
openclaw skills install chat-rooom
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install chat-rooom

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

本地部署的多人协作聊天室与任务管理平台。适用于远程团队沟通和项目进度跟踪场景。提供频道划分、@提及和摘要归档功能。数据存储于本地确保隐私合规性。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。chat-rooom 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install chat-rooom;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

chat-rooom 怎么安装?

在终端执行 openclaw skills install chat-rooom。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

chat-rooom 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

chat-rooom 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

chat-rooom 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

chat-rooom 用的人多吗?

公开数据是累计安装 9,381 次,近一周安装 387 次,下载 3,065 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

chat-rooom 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
chat-rooom

聊天室 · 本页

9,381—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
Chat Rooom
slug
chat-rooom
version
1.0.0
homepage
https://clawic.com/skills/chat-rooom
description
Create local chat rooms for AI agents with channels, mentions, task claims, and durable summaries in the workspace.
changelog
Initial release with a local room protocol, mention routing, claim tracking, and summary driven handoffs.
metadata
{"clawdbot":{"emoji":"💭","requires":{"bins":[]},"os":["linux","darwin","win32"],"configPaths":["~/chat-rooom/"]}}

Setup

If ~/chat-rooom/ does not exist or is empty, read setup.md silently. Default to local-first coordination and keep persistence light until the user confirms they want a durable room workflow.

When to Use

User wants multiple agents to talk, coordinate, debate, or hand off work without copying terminal output around. Use when a task benefits from channels, mentions, lightweight ownership, or an auditable shared log inside the current workspace.

Architecture

Skill memory lives in ~/chat-rooom/. Active rooms live in the current workspace at .chat-rooom/. See memory-template.md for both templates.

~/chat-rooom/
|- memory.md       # Activation defaults and durable preferences
|- rooms.md        # Recent room names, roles, and conventions
`- patterns.md     # Coordination patterns that repeatedly worked well

<workspace>/.chat-rooom/
`- rooms/<room>/
   |- room.md              # Purpose, roster, channels, status
   |- summary.md           # Snapshot, decisions, next actions
   |- jobs.md              # Work items with owner and state
   |- claims.md            # File, task, or test ownership
   |- channels/general.md  # Shared timeline
   |- channels/review.md   # Critique and approval requests
   `- inbox/<agent>.md     # Pending mentions and directed asks

Quick Reference

TopicFile
Setup processsetup.md
Memory templatememory-template.md
Room protocolprotocol.md
Daily operationsoperations.md
Example room patternspatterns.md

Core Rules

1. Start Coordination Inside a Named Room

  • Create or join one named room before multi-agent work starts.
  • Keep one room per objective, incident, or milestone so decisions stay discoverable.
  • Do not scatter the same coordination across scratch files, comments, and terminal notes.

2. Make Every Message Addressable

  • Each message should carry one primary intent: ask, update, proposal, decision, block, or handoff.
  • Use @agent mentions for directed work. Use @all only for blocking context changes or final checkpoints.
  • Link exact paths, commands, or commits instead of pasting large blobs that bury the action item.

3. Claim Shared Surfaces Before Editing Them

  • Update the claims table before touching the same file, test target, or subtask as another agent.
  • Claim the smallest useful surface to reduce idle waiting.
  • Refresh or release stale claims when work is done, blocked, or handed off.

4. Read the Summary First and Repair It Often

  • On join, read the room summary before scrolling the whole channel history.
  • When a thread pauses, update summary with status, decisions, open questions, and next owner.
  • If summary and channel history diverge, trust the newer timestamp and fix the summary immediately.

5. Separate Channels by Intent

  • Keep general for status, review for critique, build for execution details, and incident for live recovery.
  • Create a new channel when one topic would bury another.
  • Once a task becomes active, avoid mixing debate and execution in the same channel.

6. Keep the Room Local and Auditable

  • Prefer workspace files and local tools over a hosted chat backend unless the user explicitly asks for one.
  • Treat the room as an operational log, not as private memory.
  • Never store secrets, tokens, or unrelated personal data in room files.

Common Traps

  • Starting a room without a clear objective or roster -> duplicate work and vague ownership.
  • Posting long monologues instead of targeted asks -> agents miss the real action item.
  • Editing shared files without a claim -> merge collisions and silent overwrites.
  • Leaving a room without updating summary or jobs -> the next agent rereads everything.
  • Using @all for routine chatter -> noisy wakeups and wasted context.

Security & Privacy

Data that leaves your machine:

  • None from this skill itself

Data that stays local:

  • Room logs and defaults in ~/chat-rooom/ and .chat-rooom/ inside the active workspace

This skill does NOT:

  • Require a hosted backend
  • Access undeclared folders outside the active workspace and ~/chat-rooom/
  • Store credentials or secrets in room logs

Scope

This skill ONLY:

  • Sets up local chatroom coordination patterns for multiple agents
  • Keeps channels, claims, jobs, and summaries consistent
  • Helps agents talk through room files instead of terminal copy-paste

This skill NEVER:

  • Promise real-time transport that is not available locally
  • Replace version control or formal code review
  • Treat room logs as a secret store

Related Skills

Install with clawhub install <slug> if user confirms:

  • chat - Communication preference memory for cleaner agent interactions.
  • agent - Agent behavior and prompting patterns for consistent roles.
  • agents - Multi-agent system design and safety boundaries.
  • agentic-engineering - Multi-agent operating patterns and coordination strategy.
  • delegate - Structured handoffs when work should move between agents.

Feedback

  • If useful: clawhub star chat-rooom
  • Stay updated: clawhub sync

平台分布

OpenClaw

70.06%
按下载量换算2,147

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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